Data Engineer
Trexquant
Data Engineer
Trexquant
Quantitative trading via ML models
Trexquant Investment · Beijing, China (Hybrid) · Full-time · Posted 2026-10-08
Workplace: hybrid
Trexquant is seeking an experienced Data Engineer to build and maintain the core data infrastructure that powers our quantitative research platform. This role is responsible for owning the ingestion, normalization, storage, and ongoing maintenance of large-scale financial and alternative datasets from hundreds of global vendors.
The successful candidate will develop scalable data pipelines that transform raw vendor feeds into clean, consistent, research-ready datasets for systematic researchers and simulation platforms. Working closely with quantitative researchers, data platform engineers, and infrastructure teams, this person will ensure that market, reference, and alternative data is accurate, reliable, and readily accessible across asset classes including equities, options, futures, fixed income, ETFs, and foreign exchange.
This is an ideal opportunity for an engineer who enjoys solving complex data engineering challenges in a research-driven environment where data quality, scalability, and performance directly impact alpha generation.
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Trexquant is a quantitative finance firm that builds multi-asset portfolios using machine learning. It develops investment and research tools that ingest a wide range of data variables to create complex trading models and strategies, which in turn generate trading signals. These signals guide decisions across global markets. The product works by applying advanced machine learning to large datasets to create predictive models and rule-based strategies, which drive portfolio construction and trading actions through the firm’s platform. Trexquant differentiates itself by emphasizing the breadth of data it uses and the depth of machine-learning driven models to craft multi-asset portfolios, aiming to produce signals that outperform global market conditions. The company’s goal is to generate investment performance that beats benchmarks by using data-driven signals and diversified, multi-asset strategies.
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